Indentation testing is commonly used to test cartilage material properties. Using a linear biphasic material model, the determination of three material constants (aggregate modulus, Poisson's ratio, and permeability) from the test results requires an optimization or curve-fitting approach to determine a solution that best matches the experimental creep or stress-relaxation data.

The VA-Squish project developed a fast and easy way (using MATLAB) to calculate the best-fit bi-phasic constants, based on input from a standardized indentation test. This method involves creating a multi-dimensional Cartilage Interpolant Response Surface (CIRS) map from a large number of solutions obtained from finite element analyses and then searching this surface map for the closest solution. CIRS maps were generated for a range of different testing conditions.

Response surface files have been generated for a specific set of test conditions. It is recommended that anyone who is considering performing tests choose a test setup and testing parameters that exactly match one for which a response surface exists. These are given in the downloads section of this website and are listed in Table 2 of the VA-Squish User Guide.

Flat, porous indenter contact has been modeled as both frictionless and with a coefficient of static friction. The improved model which incorporates friction is a more accurate model of the experimental conditions. Additionally, the new release, v2.0, includes an improved mesh which is double biased through the radius and biased through the thickness.

Downloads

The VA-Squish download will allow researchers to determine the linear biphasic material properties of cartilage from indentation creep tests. The user will be able to produce a result similar to Figure 3 in the publication with their own experimental data.

SimTK is maintained through Grant R01GM124443 01A1 from the National Institutes of Health (NIH). It was initially developed as part of the Simbios project funded by the NIH as part of the NIH Roadmap for Medical Research, Grant U54 GM072970.